Merge pull request #289876 from dominicbetts/release-aio-ga-tutorial-updates

AIO [GA]: tutorial updates to use metadata

Author: v-dirichards

articles/iot-operations/end-to-end-tutorials/media/tutorial-add-assets/create-asset-details.png

@@ -115,6 +115,7 @@ To create an asset, select **Create asset**. Then enter the following asset info
 | Asset Endpoint | `opc-ua-connector-0` |
 | Asset name | `thermostat` |
 | Description | `A simulated thermostat asset` |
+| Default MQTT topic | `azure-iot-operations/data/thermostat` |
 
 Remove the existing **Custom properties** and add the following custom properties. Be careful to use the exact property names, as the Power BI template in a later tutorial queries for them:
 

articles/iot-operations/end-to-end-tutorials/media/tutorial-upload-telemetry-to-cloud/dataflow-complete.png

@@ -137,18 +137,22 @@ To create the dataflow:
     |-----------|--------------------|
     | Tag 10.Value    | ThermostatHumidity          |
     | temperature.Value | ThermostatTemperature       |
+
+1. To copy the asset ID from the message metadata, add the following rename transform:
+
+    | Datapoint | New datapoint name |
+    |-----------|--------------------|
+    | $metadata.user_property.externalAssetId | AssetId |
 
     The rename transformation looks like the following screenshot:
 
     :::image type="content" source="media/tutorial-upload-telemetry-to-cloud/rename-transform.png" alt-text="Screenshot of the rename transformation.":::
 
     Select **Apply**.
 
-1. To add an asset ID field to the message, select the **Transforms** box in the editor and then select **+ Add** in the **New property** tile.
-
-1. In the **New property** editor, enter *AssetId* as the property key, *thermostat-01* as the property value, and select **Apply**. The dataflow editor now looks like the following screenshot:
+1. The dataflow editor now looks like the following screenshot:
 
-    :::image type="content" source="media/tutorial-upload-telemetry-to-cloud/dataflow-complete.png" alt-text="Screenshot of the dataflow.":::
+    :::image type="content" source="media/tutorial-upload-telemetry-to-cloud/dataflow-complete.png" alt-text="Screenshot of the completed dataflow.":::
 
 1. To start the dataflow running, enter *tutorial-dataflow* as its name and then select **Save**. After a few minutes, the **Provisioning State** changes to **Succeeded**. The dataflow is now running in your cluster.